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Optimizing Error Correction in Quantum Computers using Reinforcement Learning
The chapter discusses a paper that explores the application of reinforcement learning to optimize error correction in quantum computers. The hosts highlight the potential value of trial and error learning and optimization in quantum systems. They delve into the topic, acknowledging their lack of expertise, and discuss the implications of using machine learning in advanced technologies like quantum computers.